Asymptotic description of stochastic neural networks. II: Characterization of the limit law (Q467695)

This is the second part of a study on asymptotic stochastic neural networks. Part I [the authors, ibid. 352, No. 10, 841--846 (2014; Zbl 1305.92014)] considers the existence of a large deviation principle and the good rate function. In the present second part, the authors show the existence of a unique minimum of the rate function, equations for the minimum are provided and using the large deviation principle, some convergence results for the measures are proved. An overview on possible extensions finishes the article.NEWLINENEWLINEFor details and proofs, the reader may consult the complete version [``A large deviation principle for networks of rate neurons with correlated synaptic weights'', Preprint, \url{arXiv:1302.1029}].